a fingerprint & pin authentication to enhance … 2229-5518 a fingerprint & pin...

ISSN 2229-5518

A Fingerprint & Pin Authentication to Enhance Security At The Automatic Teller

Machines Dondo Jacqueline Akinyi Madara, Dr. George Okeyo, Dr. Michael Kimwele

Abstract- The need of money can only be satisfied when you are carrying money with you. That also increases

the risk of getting robbed. This research focuses on how to enhance security of transactions in Automatic

Teller Machine system using a multi-factor authentication system (PIN and Fingerprint). This research proposed

a highly secured Automatic Teller Machine banking system using an optimized Advanced Encryption Standard

(AES) algorithm. This research proposes two levels of security. Firstly we consider the security level at the client

side by providing biometric authentication scheme along with a password of 4-digit long. Biometric authentication

is achieved by considering the fingerprint image of the client. Secondly we ensure a secured communication link

between the client machines to the bank server using an optimized energy efficient AES processor. The

fingerprint image is the data for encryption process and 4-digit long password is the symmetric key for the

encryption process. To get a low power consuming Automatic Teller Machine, an optimized AES algorithm is

proposed in this research. In this system biometric and cryptography techniques are used together for personal

identity authentication to improve the security level.

Index Terms- AES Algorithm, AES Processor, ATM, Biometric, Cryptography, Encryption, Fingerprint, Multi-factor

—————————— ——————————

1 INTRODUCTION

1.1 Background

Masquerade attacks and other criminal activities at

ATMs have become a nationwide issue that faces

not only customers, but also bank operators.

According to Richard et al (2006) these financial

crime cases rises repeatedly in recent years. A lot of

criminals tamper with the ATM terminal and steal

customers’ card details by illegal means. Once

users’ bank card is lost and the password is stolen,

the users’ account is vulnerable to attack. Traditional

ATM systems authenticate generally by using a card

(credit, debit, or smart) and a password or PIN which

no doubt has some defects (Amurthy and Redddy

2012). The prevailing techniques of user

authentication, which involves the use of passwords

and user IDs (identifiers), or identification cards and

PINs (personal identification numbers), suffer from

several limitations (Ratha et al 2001). Passwords

and PINs can be illicitly acquired by direct covert

observation. When credit and ATM cards are lost or

stolen, an unauthorized user can often come up with

the correct personal codes.

Many people use easily guessed PIN's and

passwords - birthdays, phone numbers and social

security numbers. The increase use of ATMs has

seen even the illiterate users most of whom write

down their PINs or ask for assistance at the ATMs

exposing their PINs. Recent cases of identity theft

have heightened the need for methods to prove that

someone is truly who he/she claims to be. Biometric

authentication technology may solve this problem

since a person’s biometric data is undeniably

connected to its owner, is nontransferable and

unique for every individual. The system can

compare scans to records stored in a central or local

database or even on a smart card.

Biometrics can be defined as a measurable

physiological and behavioral characteristic (Oxford

English Dictionary) that can be captured and

subsequently compared with another instance at the

time of verification. It is automated methods of

recognizing a person based on a physiological or

behavioral characteristic Ratha et al (2007). It is a

measure of an individual's unique physical or

behavioral characteristics to recognize or

authenticate its identity Schouten and Jacobs

(2009). Common physical biometrics characteristics

include fingerprint, hand or palm geometry, retina,

iris and face while popular behavioral characteristics

are signature and voice. Biometrics technologies

are a secure means of authentication because

biometrics data are unique, cannot be shared,

————————————————

Jaqueline Dondo is currently pursuing masters degree program in Computer Systems in Jomo Kenyatta University of Agriculture & Technology, Kenya, E-mail: [email protected]

Co-Author Dr. Okeyo & Dr. Kimwele are lecturers in Jomo Kenyatta University of Agriculture & Technology, Kenya

International Journal of Scientific & Engineering Research, Volume 8, Issue 4, April-2017 ISSN 2229-5518 380

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cannot be copied and cannot be lost. Bioinformatics

is an interdisciplinary scientific field that develops

methods and software tools for storing, retrieving,

organizing and analyzing biological data. As

globalization, networking, information and digital

era’s coming, the demand of high reliability of our

identity verification is growing. Among the existing

biometric methods, fingerprint biometrics can be

an affordable and accurate authentication

technology that has been already successfully and

widely employed.

This research presents a secured and an energy

efficient ATM banking system that is highly secured

system compared with the existing one. At present

most of the ATM systems use triple data Encryption

Standard (3DES). Which has some drawbacks;

such as, it is vulnerable to differential attacks and

also slow in performance. Ali et. al. (2013) This

research presents security in two ways in which both

the fingerprint image for the client side security and

the AES algorithm for the secured communication in

between. This research presents security in two

ways in which both the fingerprint image for the

client side security and the AES algorithm for the

secured communication in between. Based on

these perspectives, Advanced Encryption Standard

was accepted as a FIPS standard in November

2001, after which AES became the most popular

encryption standard all over the world. A lot of

researchers are working to improve the speed of

AES as well as the other aspects like area, latency,

power etc. To make the AES faster and securer,

some researchers introduced hardware realizations

and s-box optimizations. Today most of the

researchers involving the execution of the Advanced

Encryption Standard (AES) algorithm are fallen into

three areas: ultra-high-speed encryption, very low

power consumption, and algorithmic integrity. Fakir

et. al. (2013)

1.2 Statement of the Problem

Personal banking information is highly sensitive and

users are vulnerable while using ATMs Mohammed

(2015). Keypads in particular have been exploited

by criminals who have installed small cameras or

touch-sensitive overlays, or in some cases have

simply observed users as they have keyed in their

pins Chris (2009). The physical security of users is

also important. ATMs are open late at night but

often have limited security. Users may feel anxiety

and, in those cases, it is best that they complete

their ATM operations as quickly as possible. The

frequency at which ATM fraud is increasing and not

being detected is creating fear, anxiety and loss of

confidence in the banking sector that there is need

to improve the existing user authentication process.

Around 4,000 pages of data containing Cypriot

credit cards were found on a computer belonging to

thieves (New Europe 2008) Devices capable of

scanning bank and credit cards details were placed

on cash machine outside a supermarket in UK (BBC

News, 2006)

1.3 Justification

One of the major problems people face is the loss of

the password and not remembering it again, these

has caused a lot of damage to people and

organizations. ATM fraud has been very common in

all banks and the problems has created fear in many

costumers heart that they prefer going to the bank

to collect their money than to use an ATM, also

many people are illiterate that they don’t know how

to use the ATM card.

In the field of computer security, one of the most

damaging attacks is masquerading, in which an

attacker assumes the identity of a legitimate user in

a computer system. Masquerade attacks typically

occur when an intruder obtains a legitimate user’s

password or when a user leaves their workstation

unattended without any sort of locking mechanism

in place. It is difficult to detect this type of security

breach at its initiation because the attacker appears

to be a normal user with valid authority and

privileges. This difficulty underlines the importance

of equipping computer systems with the ability to

distinguish masquerading attacker actions from

legitimate user activities. Security especially at our

banks has been compromised. There are cases of

impersonation at the ATM machines and it would be

difficult to authenticate someone just with the ATM

card and PIN numbers. The current authentication

systems are characterized by an increasing interest

in biometric techniques. Among these techniques

are face, facial thermo gram, fingerprint, hand

geometry, hand vein, iris, retinal pattern, signature

and voiceprint. All these methods have different

degrees of uniqueness, permanence, measurability,

performance, user’s acceptability and robustness

against circumvention Akwaja (2010) finger print is

the most preferred.

Biometrics-based authentication offers several

advantages over other authentication. Fingerprint

technology in particular, can provide a much

more accurate and reliable user authentication

method. Biometrics is a rapidly advancing field

that is concerned with identifying a person based

on his or physiological or behavioral

characteristics. As the Automated Teller Machines

(ATM) technology is advancing, fraudsters are

devising different skills to beat the security of ATM

operations. Various forms of fraud are perpetuated,

ranging from: ATM card theft, skimming, pin theft,



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card reader techniques, pin pad techniques, force

withdrawals and lot more. Managing the risk

associated with ATM fraud as well as diminishing its

impact is an important issue that faces financial

institutions as fraud techniques have become more

advanced with increased occurrences. Considering

the numerous security challenges encountered by

Automated Teller Machines (ATM) and users and

given that the existing security in the ATM system

has not been able to address these challenges,

there is the need to enhance the ATM security

system to overcome these challenges. This

research focuses on how to enhance security of

transactions in ATM system using fingerprint.

Present research deals with new innovative

model for biometric ATMs which replaces card

system by biometric technology for operating

ATMs for example In a bid to address issues of

safety of customers’ funds and avoiding losses

through compromise of Personal Identification

Numbers (PIN), the apex bank, Central Bank of

Nigeria (CBN) is to introduce Biometric

authentication of Point of Sale (PoS) and Automated

Teller Machines (ATMs) by 2015 according to

Leadership New paper (10-07-2013).

1.4 Research Questions

Can the implementation of a multifactor technology

such as use of fingerprint and PIN be utilized as a

useful identifier in improving security at the ATM

machines?

Are there more benefits in using the AES algorithm

in a Bank employing a multifactor security system

that use PIN and fingerprint for their ATMs?

Will the use of biometric system for ATM

authentication be acceptable to the users?

1.5 Objectives

Broad Objective The purpose of this research is to enhance the

security of the existing ATM (Automated Teller

Machine) system by integrating the existing PIN

(Personal Identification Number) with the fingerprint.

Specific objective 1. To identify different areas that a multifactor

security system that use PIN and fingerprint

has been utilized.

2. To propose the use of fingerprint and PIN as

an authentication system in the Bank’s ATM.

3. To propose a low power consuming ATM

machine using the AES algorithm.

1.6 Scope of research

The first milestone of my research is learning the

biometrics especially the use of thumb/figure

recognition. Then we learnt how the PIN verification

methods work. Lastly we propose a multifactor

authentication model system.

1.7 Limitations of the research

Banks don’t not divulge sensitive information about

their scale of operation

Budgetary constraints

The research is based on secondary data taken

from content analysis and not the bank. This was not

accurate.

Security in banking is wide and we have limited our

research to one region. This might not represent the

nature of all banks.

Bias respondents

2 LITERATURE REVIEW

2.1 Introduction

Since security measures at ATM centers play a

significant role in preventing attacks on customers

money, several researches have proposed the used

of fingerprint in a like manner of this research, to

shift from PIN to biometric based security.

Fingerprinting has been the most widely used during

the 20th century. The maturity of Biometric

techniques and generally the dramatic improvement

of the captured devices have led to the research of

fingerprinting in multiple applications but in the last

years, minutiae have been the main type of

algorithm used. The minutiae are relatively stable

and robust to contrast, image resolution and global

distortion as compared to other fingerprint

representation Fatai et al. (2014). Jeroen et al.

(2011) provided a better understanding of the

benefits and limitation of integration of biometrics in

a PIN-base payment authentication system. Based

on their review they proposed a biometric that can

be integrated in a PIN-based authentication

infrastructure by binding a fixed binary, renewable

string to a noisy biometric sample.

2.2 Related studies

The South African Social Security Agency (SASSA)

has introduced a new SASSA Payment Card that

has a fingerprint authenticated features. The card is

a SASSA branded smart payment MasterCard,

which has an embedded chip containing personal

details, fingerprint and secret PIN, with the card the

customers can easily withdraw and make payment

at point-of-sale (POS) center, purchase airtime, pay

water and electricity bill from the accounts, or open

accounts. (SAAS, 2013).



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Wang Y. et al (2007) proposed a fingerprint

orientation model based on 2D Fourier expansions

(FOMFE) in the phase plane. Though FOMFE does

not require prior knowledge of singular points, it is

able to describe the overall ridge topology

seamlessly. Fengling et al (2005) proposed a

smartcard based encryption/authentication scheme

for ATM banking system. The first layer of the scheme is used to perform authentication based on

available information on the smartcard. Fingerprint

based authentication via feature and minutiae

matching then followed on the second layer. Das

and Jhunu (2011) focused on vulnerabilities and the

increasing wave of criminal activities occurring at

ATMs and presented a prototype fingerprint

authentication for enhancing security. The systems

adopt the same measure as the current work by

formulating modules for fingerprint enrolment,

enhancement, feature extraction and database and

matching. Santhi and Kumar (2012) proposed an

ATM security enhancing method with secured

Personal Identification Image (PII) process. A

detailed research on various existing biometric

systems is also presented stating the strengths and

limitations. Bhosale and Sawant (2012) and Ibiyemi

et al (2012) present groundbreaking models for

biometric ATMs which replaces card system with

biometric technology. The proposed systems

hybridize feature-based fingerprint, iris and PIN to

provide reliable and fool-proof ATM authentication.

Customers must be convinced that the technologies

provide more benefit than the card-and-PIN system,

which works well, said John Hall, spokesman for the

American Bankers Association. The cards also

serve functions beyond the ATMs, as debit cards

and as advertising for the banks. "Getting that wallet

space is important," said Bill Spence, a biometric

expert with Campbell, Calif.-based Recognition

Systems Inc. The growers wouldn't need to carry

ATM cards, which can be a lure for thieves.

"Biometrics is certainly the most secure form of

authentication," said Avivah Litan, an analyst with

Gartner Inc., a Stamford, Conn.-based technology

analysis firm. "It's the hardest to imitate and

duplicate." Jain, A.et. al. (2000)

However, companies that make automated teller

machines have found budding markets for the

fingerprint technology in South America, where

citizens already are accustomed to the use of

fingerprints for general identification, such as ID

cards they carry. Diebold Inc. of North Canton, Ohio,

has supplied fingerprint-capable ATMs to a bank in

Chile that is using them in a pilot project. Last year

Dayton, Ohio-based NCR Corp. installed 400 of

them in Colombia. BanCafe, Colombia's fifth largest

bank, bought the ATMs at the end of 2002 for added

security for coffee growers and to get them to open

accounts.

Mali et al (2012) provided a network security

framework for real time ATM application using a

combination of PIN, thumb scanning and face

recognition to foster security. The proposed

framework is expected to register thumb and face

features to be stored at a server side in encrypted

format. Authentication is done by decrypting

patterns from database, and matching with input

pattern before access is granted for ATM

operations. The integrated system uses Principal

Component Analysis (PCA) and Eigen algorithm for

face recognition, LSB algorithm for stegnogaphy

and AES algorithm for cryptography. Though the

framework looks promising, its practicality is not

supported by detailed implementation and

evaluation. Abayomi et al (2012) proposed an

enhanced e-banking system where customer can

access multiple accounts over different banks

institutions with a single ATM card with fingerprint

authentication. A match-on-card technique was

used that relies on a one-to-one matching where the

data from the ATM fingerprint sensor is compared

only to the template stored on the user’s ATM card.

This will help in privacy concern of users; the system

will also help the users to have access to multiple

accounts with a single ATM card. It is secured and

help in reducing ATM fraud. This research presents

security in two ways. This design considers the

fingerprint image for the client side security and also

considers the AES algorithm for the secured

communication in between the client and server. A

lot of researchers are working to improve the speed

of AES as well as the other aspects like area,

latency, power etc. To make the AES faster and

securer some researchers introduced hardware

realizations and s-box optimizations. Today most of

the researchers involving the execution of the

Advanced Encryption Standard (AES) algorithm are

fallen into three areas: ultra-high-speed encryption,

very low power consumption, and algorithmic

integrity. Many research works have been done by

different hardware realizations using ASIC and

FPGA technology. Some References present the

fastest FPGA realization of the AES algorithm.

Fingerprint based authentication is more secure,

reliable and standard than the password based

authentication. Finger-scan biometric is based on

the distinctive characteristics of the human

fingerprint. Our existing ATM system is password

based. The limitation of this system is that it fails to

identify the person rather it only identify the card and

password as well as the communication link is not

secured. , which have access to be hacked. The

proposed ATM system is able to overcome this type



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of limitations because proposed ATM system is

fingerprint based.

2.3 Identified Gap

AT present most of the ATM systems use triple-data

Encryption Standard (DES) Nawaz et. al.(2013) but

the triple-DES has some drawbacks. It is vulnerable

to differential attacks and also slow in performance.

DES (Data Encryption Standard) has been used as

a de facto standard cipher for more than 20 years.

In 2001, NIST (National Institute of Standards and

Technology) made Rijndael the new standard cipher

AES Daemen and Rijmen (2001), NIST (2001).

Personal banking information is highly sensitive and

users are vulnerable while using ATMs Mohammed

(2015). Keypads in particular have been exploited

by criminals

2.4 A conventional ATM system

ATM is the abbreviation of "Automated Teller

Machine". This machine allows the account holder

to have transactions with their own accounts without

allowing them to access the entire bank's database.

The idea of self-service in retail banking was

developed through independent and simultaneous

efforts in Japan, Sweden, the United Kingdom and

the United States. In the USA, Luther George

Simjian has been credited with developing and

building the first cash dispenser machine. The first

cash dispensing device was used in Tokyo in 1966.

Figure 1 A Conventional ATM System

ATM first came into use in December 1972 in the

UK. IBM 2984 was designed for request of Lloyds

Bank. ATM is typically connected directly to their

hosts or ATM Controller via either ADSL or dial-up

modem over a telephone line or directly via a leased

line. For transaction security all communication

traffic between ATM and transaction process is

encrypted by cryptography. Nowadays, most of ATM

uses a Microsoft OS primarily Windows XP

Professional or Windows XP Embedded or Linux.

2.5 Fingerprint

Fingerprint is a characteristic which is unique for

each person. Every fingerprint contain unique

identifiable piece of information. The uniqueness in

each fingerprint is due to the peculiar genetic code

of DNA in each person. Ridges and valleys are the

parts of fingerprint that provide friction for the skin.

The direction and location of ridges make the

identification. A fingerprint in its narrow sense is an

impression left by the friction ridges of a human

finger. In a wider use of the term, fingerprints are the

traces of an impression from the friction ridges of

any part of a human. There are three types of

fingerprint patterns.

2.6 AES Algorithm

The Rijndael algorithm referred to as the AES

Algorithm, is a symmetric key block cipher that can

process data blocks of 128 bits, using cipher keys

with lengths of 128, 192, and 256 bits. Figure 2

shows that AES has four stages which are required

for every round except that the last round excludes

the mix column phase and the first round has only

key addition.

The four stages of Rijndael algorithm (AES

algorithm) are:

Substitute bytes: This function uses an S-box to

perform a byte-by-byte substitution of the block.

For encryption and decryption, this function is

indicated by SubBytes () and InvSubBytes ()

respectively.

Shiftrows: This is a simple permutation. For

encryption and decryption, this function is

indicated by ShiftRows () and InvShiftRows ()

respectively.

Mix Columns: This is a substitution that makes

use of arithmetic over GF (28), with the

irreducible polynomial “m(x) = x8 + x4 + x3 + x

+1”. For encryption and decryption, this function

is indicated by MixColumns () and

InvMixColumns () respectively.



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Add round key: This function does a bitwise

XOR operation of the current block with a

portion of the expanded key. For both

encryption and decryption this function is

indicated by AddRoundKey (). For the

AddRoundKey () stage, the inverse is achieved

by XORing the same round key to the block,

using the result: A ⊕A⊕ B = B.

3 RESEARCH METHODOLOGY

3.1 Introduction

The methodology proposed by Webster and Watson

(2002) was followed. In the subsequent pages of

this chapter, the steps taken to identify relevant

literature is presented, along with the results of this

procedure. The purpose of this research is to

present a secured and an energy efficient ATM

banking system that is highly secured. At present

most of the ATM systems use triple-data Encryption

Standard (DES) but the triple-DES has some

drawbacks. It is vulnerable to differential attacks and

also slow in performance. Nawaz (2013). This

research presents security in two ways, a design

that considers the fingerprint image for the client

side security and also consider the AES algorithm

for the secured communication in between the client

and server. Reducing the power consumption of

AES (Advanced Encryption Standard) circuits is a

critical problem when the circuits are used in

embedded systems. Many circuit architectures for

AES have been proposed recently and their

performances have been evaluated by using ASIC

libraries Kuo et al. (2001), However, most of them

are simple implementations according to the AES

specification, and there is no report of low-power

AES implementations, as far as the authors know.

In this research, we investigated a design

methodology for a low-power AES. Although many

power reduction techniques for IP cores are known

for various design abstraction levels from the

algorithm level to the transistor level Chandrakasan

and Brodersen (2007)[2], we focused on the logic

level (gate level), because the power optimization

techniques at this level can be applied in many

applications. The optimizations at the other levels

cannot be adopted as often, because the AES circuit

is usually used as an IP core in a system, and

changing the algorithm, operator scheduling, data-

path architecture, and/or arrangements of

transistors of the AES is difficult under given

requirements for throughput, clock speed, and

technology library Morioka and Akashi (2014).

Security has become a great issue in every part of

life. Passing of information faces massive problems

due to various types of attacks into the

communication link. The biometric authentication

process adds a new dimension of security for any

person sensitive to authentication. In this chapter

we describe the research methodology of this

research, explain the sample selection, describe the

procedure used in designing the instrument and

collecting the data, and provide an explanation of

the statistical procedures used to analyze the data.

3.2 Research design

A descriptive research methodology is used for this

research because it portrays accurately that most

ATM users have no confidence in the use of PIN as

the only means of identity at the ATM machines, by

conducting a survey and fact finding. We used some

survey methods like comparative and correlation

approach conducting survey on users and also

existing literature. This research has some aspects

of qualitative methods where the users opinions and

attitude is used to come up with the conclusions

about the use of PIN and biometric at the ATM.

Gravetter and Forzano (2011) explain that

descriptive research design involves the

measurement of a variable or a set of variables as

they naturally exist. The research is aimed at

collecting information from respondents in

determining e-learning security issues. Chandran

(2004) notes that descriptive research designs are

used in studies that answers the “who”, “what”,

“when”, “where” and “how” questions. This design

describe what is prevalent in security challenges in

ATM systems. The use of descriptive research

design enabled the description of the identification

Figure 2 Proposed ATM System



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of security issues affecting ATM system in banking

sector in Kenya. A survey is administered to a

selected sample from Machakos. The term ‘survey’

is commonly applied to a research methodology

designed to collect data from a specific population,

or a sample from that population, and typically

utilizes a questionnaire or an interview as the survey

instrument (Robson, 1993)

3.3 Research population

The total population of the research is banks that are

in Machakos County. Machakos County has an

estimated population of 1,098,584 people

machakos county profile (2015) which includes five

towns; Athi River, Machakos, Kangundo-Tala,

Kathiani and Masii. The target population is the ATM

users which the researcher is interested in

describing and making statistical inferences about.

It refers to the entire group of individual or objects to

which researchers are interested in generalizing the

conclusion.

3.4 Sample and sampling techniques

For this research, my sampling unit is geographical

where Machakos town is sampled. The

methodology for this research is a stratified random

sample of bank users across the town. Gay (1987)

reports: Random sampling is the best single way to

obtain a representative sample.

3.5 Data collection instruments

This research had two sets of data, the primary data

and the secondary data. The primary data was

collected using questionnaires and personal

interviews directly from the ATM users and a central-

site intercept survey in which potential audience

members were approached in a public area and

asked to respond to a quick questionnaire. The

research was conducted on an existing group,

numerical data is collected Data for this research is

obtained through the following: Questionnaire: this

is administered on the customers and staff of the

selected banks. This involves close-response

questions with only ‘yes’ or ‘no” answers to assist in

carrying out the research. Personal Interview: for all

the technical questions the secondary data is

collected mainly from Library research or content

analysis. This aids in consulting relevant literature

already written on the subject

3.6 Data analysis

Data analysis involved editing, coding, classification

and tabulating of the data collected. The editing is

done by me scrutinizing questionnaires to detect

errors and omissions then translate or rewrite the

responses especially because some handwritings

might not be clear, this was achieved by conducting

a field editing where clarity is made as the data is

being collected. Centralized editing after the data is

collected. The analysis is done by SPSS and there

was need of assigning numerical values to the

answers given during data collection for the sake of

coding and classification using tables to tabulate the

findings to summarize the survey.

Acknowledgments

I thank God almighty for giving me patience,

knowledge and understanding and most importantly

for giving me life. I thank Dr. Kimwele and Dr. Okeyo,

Lecturers at Jomo Kenyatta University of agriculture

and Technology for guiding me through my

research, to my mother Foska Dondo for her

encouragement.

REFERENCES

[1] (AES)”, FIPS Publication 197,

http://csrc.nist.gov/encryption/ aes/index.html,

Nov. 2001.

[2] A.P. Chandrakasan and R.W. Brodersen (eds.),

Low Power Digital CMOS Design, Kluwer

Academic Publishers, 2005.

[3] Abayomi-Alli A., Omidiora E.O., Olabiyisi E.O.,

and Ojo J.A., Enhanced E-Banking System with

Match-On-Card Fingerprint Authentication and

MultiAccount ATM Card. The Journal of

Computer Science and Its Aplication, An

International Journal of the Computer Society of

Nigeria (NCS), V0l. 19, No.2 December, 2012

[4] Akwaja Chima, Nigeria Connects 99 million

Subscribers, Fin. Standard., 2010, 10: 15-512.

[5] ATM scam targets hundreds of credit cards‘,

New Europe, issue: 793, 4 August 2008, From

http://www.neurope.eu/articles/89221.php (last

visited on 20 April 2009).

[6] B, Schouten and B. Jacobs, Biometrics and

their use in e-passport, Image and Vision

Computing vol. 27, pp. 305–312. 2009,

[7] B. Richard and M. Alemayehu, Developing E-

banking Capabilities in a Ghanaian Bank:

Preliminary Lessons. Journal of Internet

Banking and Commerce, vol. 11, no. 2, 2006.

Downloaded March 15, 2012 from

http://www.arraydev.com/commerce/jibc/

[8] Bhosale ST, and Sawant BS, Security in

eBanking via Card-less Biometric ATMS.

International Journal of Advanced Technology &

Engineering Research, 2012, 2: 9-12.

[9] Chris. Christian Science Monitor. ‘Guard your

card: ATM fraud grows more sophisticated’.

July 23, 2003.From

http://www.csmonitor.com/2003/0721/p15s01-



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wmcn.html

[10] Das SS, and Jhunu D, Designing a Biometric

Strategy (Fingerprint) Measure for Enhancing

ATM Security in Indian E-Banking System.

International Journal of Information and

Communication Technology Research, 2011,

197-203.

[11] Fatai, O.W., Awotunde, J.B. and Matluko, O.E,

A Novel System of Fingerprint Recognition

Approach for Immigration Control, IOSR

Journal of Computer Engineering (IOSR-JCE)

2278-8727Volume 16, Issue 3, Ver. III (May-

Jun. 2014), PP 39-42.

[12] Fengling H, Jiankun H, Xinhuo Y, Yong F, and

Jie Z, A novel Hybrid Crypto- Biometric

Authentication Scheme for ATM Based Banking

Applications. Lect Notes Comput Sci, 2005,

3832: 675-681.

[13] H. Kuo et al., "Architectural Optimization for a

1.82 Gbits/sec VLSI Implementation of the AES

Rijndael Algorithm," Proc. CHES2001, LNCS

Vol. 2162, pp. 53–67, 2001

[14] http://leadership.ng/news/100713/cashless-

policy-cbnintroduce-biometrics-atms-pos-

2015#sthash .I0I5wd2G.dpuf Leadership New

paper, 10-07-2013.

[15] Ibiyemi T. S, Obaje S. E, and Badejo J

Development of Iris and Fingerprint Biometric

Authenticated Smart ATM Device & Card. 24th

National Conference of the Nigeria Computer

Society (NCS), 2012.

[16] J. Daemen and V. Rijmen, “AES Proposal:

Rijndael,” http://csrc.nist.gov/

encryption/aes/rijndael/Rijndael.pdf.

[17] Jain, A., Hong, L., & Pankanti, S. (2000).

Biometric Identification, Communications of the

ACM, 43(2), p. 91-98.

[18] Jeroen B., Ileana B., Koen G., and Emile K.,

Evaluation of a template protection approach to

integrate fingerprint biometrics in a PIN-based

payment infrastructure, 2011.

[19] Kuykendall, Lavonne and W. A. Lee,

Intermediary Risk? Card Hack Puts OSOs in

the Hot Seat, American Banker, February 21

2003.

[20] M. Theofanos, B. Stanton, and C. A. Wolfson,

Usability & Biometrics: Ensuring Successful

Biometric Systems. National Institute of

Standards and Technology (NIST), 2008.

[21] Machakos county profile, from

http://www.machakosgovernment.com/Machak

osProfile.aspx last visited on 10 October 8,

2015

[22] Mali P, Salunke S, Mane R, and Khatavkar P.,

Multilevel ATM Security Based On Two Factor

Biometrics, 2012, IJERT 1: 8.

[23] N.K. Ratha, J.H. Connell, and R.M. Bolle,

Enhancing Security and Privacy in Biometrics-

based Authentication Systems, IBM Systems

Journal, vol. 40, no. 3, pp. 614-634, 2001.

[24] N.K. Ratha, S. Chikkerur, J.H. Connell and R.M.

Bolle. Generating Cancelable Fingerprint

Templates”, IEEE Transaction on Pattern

Analysis and Machine Intelligence, vol. 29, no.

4, 2007.

[25] National Institute of Standards and Technology

(NIST), “Advanced Encryption Standard

[26] P.K. Amurthy and M.S. Redddy, Implementation

of ATM Security by Using Fingerprint

recognition and GSM, International Journal of

Electronics Communication and Computer

Engineering vol.3, no. 1, pp. 83-86, 2012.

[27] Santhi B, and Kumar RK, Novel Hybrid

Technology in ATM Security Using Biometrics.

Journal of Theoretical and Applied Information

Technology, 2012, 37: 217-223.

[28] Shoppers are targeted in ATM scam‘, BBC

News, 11 March 2006, available at

http://news.bbc.co.uk/2/hi/uk_news/england/te

es/4796002.stm (last visited on 20 April 2009).

[29] Swann, J., Teaching Ethics: It's the Right Thing

to Do. OR/MS Today, 2004, 31:10.

[30] The South African Social Security Agency

(SASSA), A leader in the delivery of social

security services. Re-register to get yours:

SASSA HOUSE 501 Prodinsa Building Cnr

Steve Biko and Pretorius Street Pretoria, 2013.

[31] Travel Guide for Your Finances. ‘Card Fishing

ATM Scam’. Card Fishing ATM Scam.

December 27, 2006. From

http://www.travelfinances.com/blog/index.php/

2006/12/27/card-fishing-atm-scam/

[32] U. Uludag, Secure biometric systems, Ph.D.

dissertation, Michigan State University, 2006.

[33] Wang Y, Hu J, and Phillips D, A fingerprint

orientation model based on 2D Fourier

expansion (FOMFE) and its application to

singular-point detection and fingerprint

indexing. IEEE Trans Pattern Anal Mach Intell,

2007, 29: 573-585.

[34] Webster, J. & Watson, R.T. (2002). Analyzing

the Past to Prepare for the Future: Writing a

Literature Review. MIS Quarterly, 26(2), pp. xiii-

xxiii. West, D.M. (2004).



IJSER

http://helios.et.put.poznan.pl/~dgajew/download/PUT/SEMESTR_10/IO/FACE_RECOGNITION/BiometricsACM.pdf

http://helios.et.put.poznan.pl/~dgajew/download/PUT/SEMESTR_10/IO/FACE_RECOGNITION/BiometricsACM.pdf

http://www.machakosgovernment.com/MachakosProfile.aspx

http://www.machakosgovernment.com/MachakosProfile.aspx

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